Hend Farahat Issa Farag2023-02-022023-02-022022https://hdl.handle.net/10115/21118Tesis Doctoral leída en la Universidad Rey Juan Carlos de Madrid en 2022. Directoras: Lydia González-Serrano y Pilar Talón-BallesteroThe objective of the study is to delve into new forms of pricing from the point of view of hotel Revenue Management (RM). The introduction of big data technology in hotel RM systems has contributed to a new way of setting prices in the hotel industry called 'Open Pricing' (OP). The OP application is based on the use of a large amount of data (big data) that facilitates sophisticated price discrimination in real-time, without rate ranges and restrictions, based on the customer's willingness to pay (WTP). This study aims to increase the knowledge of the application of OP in the hotel sector. It also seeks to determine if the OP increases the hotel's revenue. The research determined to what extent OP improves the revenue of independent hotels by increasing RevPAR. To do this, the study analyses the pricing of three independent hotels before the OP, called "variable dynamic pricing" and compares it with the two years following the implementation of the OP. Therefore, the present study uses a longitudinal approach of three quasi-experiments, employing the analysis of variance test to compare three years of data in the three chosen independent hotels. The study measures revenue one year before the OP (2017) application and two years after it (2018 and 2019). The work compares revenue performance variation with that of the competition to eliminate external factors that may affect revenue change. The performance of the competitor’s hotels has been collected from the National Institute of Statistics (INE). The analysis finds that OP hotels earn higher revenues after applying OP compared to the previous practice of "variable dynamic pricing". Additionally, all three hotels have higher RevPAR variation than their competitors. Thus, OP hotels adjust better to fluctuations in demand. On the other hand, the research develops a conceptual and theoretical analysis through its chapters. Therefore, the study examines and extends the developing body of literature on RM and price discrimination (PD) theories, First, the study reviews the concept of RM, the characteristics necessary for its implementation, and its strategies. Then, the research provides knowledge of the economic theory of the PD and its degrees and analyses the dynamic hotel rates. Next, the study examines the development phases of pricing in the hotel RM, focusing on the OP application to broaden its understanding. Finally, the study analyses and extends the literature review on the benefits of dynamic pricing on hotel results. This research provides empirical evidence that OP improves OR, ADR, and RevPAR, justifying the use of OP in independent hotel RM systems; it is one of the few empirical studies that analyses the impact of OP on the performance of independent hotels.engAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Open pricingdynamic pricingbig dataindependent hotelsRMinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/embargoedAccess